Mobile reception in OFDM (orthogonal frequency-division multiplexing) systems has received increasing attention with the growing demands for applications such as for communication in high speed railways. In mobile OFDM systems, the accurate estimation and tracking of time-varying and frequency selective fading is critical to the design of the frequency domain equalization and detection. Pilots can be inserted in transmitted OFDM symbols to assist channel estimation in various standards, e.g., scattered and edge pilots are inserted in time and frequency directions to assist channel estimation in the second generation digital terrestrial television broadcasting system (DVB-T2) and advanced television systems committee (ATSC) 3.0 systems. Channel estimations are used to operate the frequency domain equalizer to improve signal reception.
Generally, the receiver first obtains estimates of the channel frequency response using pilot sub-carriers, then interpolates this response to provide a channel estimate for the data sub-carriers. The channel estimate is applied to the equalizer in the receiver and is subsequently updated to track changing channel conditions. In the frequency domain the data sub-carriers can be estimated using a time-frequency two-dimensional (2D) filter to get a good estimation of the data, but this technique results in high computation complexity. Thus two one-dimensional (1D) filters, the first one for time direction interpolation and the second for frequency direction interpolation, may be used alternatively although with a slight performance loss. The channel estimator disclosed herein can be applied to the time-frequency 2D estimation, 1D time direction estimation and 1D frequency direction estimation, respectively.
Frequency domain interpolation may be performed using many different interpolation techniques such as linear, cubic and spline interpolations or a combination thereof. Linear interpolation is popular in practical implementations due to its low complexity, but provides relatively poor performance. Due to the nature of broadcast RF (radio frequency) signals, there are some similarities between different channel coefficients even when the channel experiences fast changes. These similarities may be quantified by a function referred to as channel correlation. Exploiting the channel correlation and noise variance characterizing a given channel, a MMSE (minimum-mean-square error) estimator can significantly improve the estimation accuracy of the data sub-carriers. However, two constraints impede the implementation of the MMSE estimator in a practical system. The first is that the channel statistics and noise variance is usually unknown, especially in a mobile scenario. The second is the high computing complexity caused by the matrix inversion operation in the MMSE. Many prior art works focus on the design of a practical MMSE estimator to overcome one or both of the above two constraints.
Corresponding to the first constraint, channel estimators have been proposed by either constructing a reference channel model or by real-time estimation of the current channel statistics. An ideal band-limited time domain correlation and a rectangular delay profile have been suggested for estimators incorporating the reference channel model. Similarly, a uniform power delay profile has been used in the cases where the worst correlation is expected. The foregoing reference channel models are insensitive to variations in channel statistics and are relatively simple to implement. Another method is to roughly estimate the actual current channel correlation and then design the MMSE estimator to be adaptive to the current channel. An extra computing effort is required to obtain the accurate channel model, thus implementation complexity is increased.
In case of the reference model based MMSE channel estimator, due to fast fading variations, channel model mismatch errors (MME), i.e., the errors caused by the difference between the reference channel model and the real channel, are usually inevitable in practical mobile communication systems. Designing a MMSE estimator that is naturally tolerant of this mismatch provides significant improvement over the prior art estimators.
Turning to the second constraint, various techniques have been proposed to reduce the complexity of the MMSE estimator, such as singular value decomposition (SVD), which works for the block-type pilots with the assumption of perfect channel correlation. U.S. Pat. No. 7,801,230, in order to reduce complexity, discloses the use of a split MMSE (S-MMSE) that separates the sub-carriers into groups, and a separate filter is applied into each sub-group independently. However, some significant limitations hinder implementation of this application. First, the proposed method only works for block type pilots. It does not work for comb-type pilots such as those in DVB-T2 or ATSC 3.0. Second, it is assumed the channel statistics are perfectly known, while the perfect prior information is not available in mobile OFDM systems. Finally, the window size obtained under the ideal channel correlation assumption does not work well for systems with channel model mismatch.